Brushless direct current (BLDC) motors are mostly preferred for dynamic applications such as automotive industries, pumping industries, and rolling industries. It is predicted that by 2030, BLDC motors will become mainstream of power transmission in industries replacing traditional induction motors. Though the BLDC motors are gaining interest in industrial and commercial applications, the future of BLDC motors faces indispensable concerns and open research challenges. Considering the case of reliability and durability, the BLDC motor fails to yield improved fault tolerance capability, reduced electromagnetic interference, reduced acoustic noise, reduced flux ripple, and reduced torque ripple. To address these issues, closed-loop vector control is a promising methodology for BLDC motors. In the literature survey of the past five years, limited surveys were conducted on BLDC motor controllers and designing. Moreover, vital problems such as comparison between existing vector control schemes, fault tolerance control improvement, reduction in electromagnetic interference in BLDC motor controller, and other issues are not addressed. This encourages the author in conducting this survey of addressing the critical challenges of BLDC motors. Furthermore, comprehensive study on various advanced controls of BLDC motors such as fault tolerance control, Electromagnetic interference reduction, field orientation control (FOC), direct torque control (DTC), current shaping, input voltage control, intelligent control, drive-inverter topology, and its principle of operation in reducing torque ripples are discussed in detail. This paper also discusses BLDC motor history, types of BLDC motor, BLDC motor structure, Mathematical modeling of BLDC and BLDC motor standards for various applications.INDEX TERMS BLDC motor, torque ripple, current shaping techniques, controlling input voltage, direct torque control, drive-inverter topology, field orientation control, motor design, fault tolerance control and electromagnetic interference reduction.

Active power losses have the potential to affect the distribution of power flows along transmission lines as well as the mix of energy used throughout power networks. Grey wolf optimization algorithms (GWOs) are used in electrical power systems to reduce active power losses. GWOs are straightforward algorithms to implement because of their simple structure, low storage and computing needs, and quicker convergence from the constant decrease in search space. The electrical power system may be separated into three primary components: generation, transmission, and distribution. Each component of the power system is critical in the process of distributing electricity from where it is produced to where it is used by customers. By using the GWO, it is possible to regulate the active power delivered by a high-voltage direct current network based on a multi-terminal voltage-source converter. This review focuses on the role of GWO in reducing the amount of active power lost in power systems by considering the three major components of electrical power systems. Additionally, this work discusses the significance of GWO in minimizing active power losses in all components of the electrical power system. Results show that GWO plays a key role in reducing active power losses and consequently reducing the impact of power losses on the performance of electrical components by different percentages. Depending on how the power system is set up, the amount of reduction can be anywhere from 12% to 65.5%.

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Demonstration of heat release phenomenon by employing the numerical approach is the main purpose of current research. Water as PCM was combined by particles and homogeneous mixture was assumed. Various shapes of powder with different concentrations were employed. The unsteady energy equation involving nanomaterial properties and freezing source term has been analyzed and for finding the solution, the Galerkin technique was employed. The adaptive grid generates greater number of elements in solid front region. Implicit formulations for unsteady terms were implemented and automatic time step was employed in software. Solid front changes with alteration of shapes of nanopowder and its fraction. With fraction augmentation, freezing finishes in lower time. The needed time diminishes by about 10.29% and 13.78%, respectively. Changing the shape of particles to the biggest level makes the period decline by less than 4.8% and 8.4%. A greater fraction of nanomaterial leads to a higher effect on the shape of nanomaterial.

Managing the timing constraints has become an important factor in the physical design of multiple supply voltage (MSV) integrated circuits (IC). Clock distribution and module scheduling are some of the conventional methods used to satisfy the timing constraints of a chip. In this paper, we propose a simulated annealing-based MSV floorplanning methodology for the design of ICs within the timing budget. Additionally, we propose a modified SKB tree representation for floorplanning the modules in the design. Our algorithm finds the optimal dimensions and position of the clocked modules in the design to reduce the wirelength and satisfy the timing constraints. The proposed algorithm is implemented in IWLS 2005 benchmark circuits and considers power, wirelength, and timing as the optimization parameters. Simulation results were obtained from the Cadence Innovus digital system taped-out at 45 nm. Our simulation results show that the proposed algorithm satisfies timing constraints through a 30.6% reduction in wirelength.